Quantile Regression Methods of Estimating Confidence Intervals for WASDE Price Forecasts

This paper explores the use of quantile regression for estimation of empirical confidence limits for WASDE forecasts of corn, soybean, and wheat prices. Quantile regressions for corn, soybean, and wheat forecast errors over 1980/81 through 2006/07 were specified as a function of forecast lead time. Estimated coefficients were used to calculate forecast intervals for 2007/08. The quantile regression approach to calculating forecast intervals was evaluated based on out-of-sample performance. The accuracy of the empirical confidence intervals was not statistically different from the target level about 87% of the time prior to harvest and 91% of the time after harvest.


Issue Date:
2008
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/6409
Total Pages:
35
Series Statement:
Selected Paper
469246




 Record created 2017-04-01, last modified 2017-04-26

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